1. Experimental Design Reaching a balance between statistical power and available finances

2. Cost of Microarrays Glass arrays €250 - €400 Affymetrix arrays €700 - €900

3. Experimental Design Choice of microarray Hybridization design Number of replicates Dye-bias RNA samples

4. Choice of Microarray Glass slide v Affymetrix In house v Commercial Oligonucleotide v cDNA Focal v Global

5. Two- Colour Microarray Designs Reference design Loop design

6. Classical Reference Design

7. Common Reference Design

8. Loop Design

9. Number of Replicates Technical replicates Biological replicates Increasing the number of replicates = –Increases statistical power. –Increases cost of the microarray experiment. –Increases animal costs.

10. Dye Bias Cy3 and Cy5 can bias binding to particular array spots. Include a dye-swap of each array to identify and remove these problems. Doubles the number of microarrays required. Cy3 Cy5

11. RNA Samples Tissue/cell type Time course Quality of RNA Quantity of RNA

12. Quality of RNA 1) Extract RNA using Trizol 2) Purify RNA using Qiagen RNeasy column 3) QC RNA using Aligent BioAnalyzer good quality RNApoor quality RNA

13. Linear Amplification of RNA Hybridization Labelling AAAA 3’ 5’ Total RNA AAAA 3’ TTTT-T7 5’ 5’ 3’ cDNA First strand cDNA synthesis AAAA-T7 TTTT-T7 3’ 5’ Transcription template Second strand cDNA synthesis UUUU 5’ Antisense RNA In vitro transcription (incorporation of amino allyl UTP)

14. Conclusions (2) Need to balance statistical power and cost. Need to reduce variation and increase the statistical power of the experiment by: –Design of the experiment –Replicate spots –Technical replicates –Biological replicates –Dye-swap Good quality RNA is essential.